The digital forest : exploring AI’s ecological footprint and sustainability challenges

Abstract

As artificial Intelligence keeps evolving, its environmental footprint has become an increasing cause for alarm. The ever-greater computational power utilized to train and deploy AI models means high energy usage, a carbon footprint, and e-waste. This thesis discusses the use of AI in Green Information Technology, considering whether it can worsen or alleviate environmental issues.

The study investigates top areas such as energy-efficient AI algorithms, sustainable hardware design, and AI-based optimization for resource allocation. It also examines AI hardware and software life cycles and their impacts on the environment. Drawing on a literature review, case study, and quantitative analysis of data, this research proposes ways to reduce AI's carbon footprint without impeding its technological advancement.

Research indicates that although AI generates sustainability challenges, the evolution of Green AI principles, green computing, and harnessing renewable energy can reduce its carbon footprint efficiently. This study adds to the narrative of sustainable AI development and demands careful policies and practices to enable AI's role in a greener digital future.